| 刘中宪,黄珑,孟思博,黄振恩.基于机器学习的IBIEM控制方程基本解构造模型[J].计算力学学报,2025,42(2):228~234 |
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| 基于机器学习的IBIEM控制方程基本解构造模型 |
| Machine learning based model for constructing basic solutions of IBIEM control equations |
| 投稿时间：2023-10-25 修订日期：2024-02-12 |
| DOI：10.7511/jslx20231025002 |
| 中文关键词: 间接边界积分方程法 虚拟波源 人工神经网络 粒子群优化 波动问题求解 |
| 英文关键词:indirect boundary integral equation method virtual wave source artificial neural network particle swarm optimization solving fluctuation problems |
| 基金项目:国家自然科学基金(52278516;52208497);天津市杰出青年基金(19JCJQJC62900)资助项目. |
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| 摘要点击次数: 12 |
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| 中文摘要: |
| 间接边界积分方程法IBIEM(indirect boundary integral equation method)求解波动问题时控制方程基本解构造依赖经验判断和试算,导致宽频散射求解不够稳定。本文通过粒子群优化-人工神经网络建立IBIEM控制方程基本解构造模型,以数据驱动代替经验判断,处理基本解构造过程中的不确定性。以二维峡谷对平面SH波散射IBIEM模拟为例验证所建模型的可靠性。结果表明,所建IBIEM控制方程基本解构造模型可对虚拟波源位置和数量的最优设置进行有效预测,兼顾计算效率和精度,大幅提高IBIEM求解波动问题时的稳定性和高效性;虚拟波源位置和数量最优设置方案受入射波频率和场地几何条件影响显著,且表现出非单调变化特征,依据经验设置基本解可靠性较差,以数据驱动的预测模型具有明显优势。本文所建方法可为IBIEM求解其他类型场地地震波动问题提供参考。 |
| 英文摘要: |
| The indirect boundary integral equation method(IBIEM)relies on empirical judgment and trial calculations to construct the basic solution of the governing equation when solving wave propagation problems,resulting in unstable solutions for wide-frequency scattering.This paper proposes a model for constructing the basic solution of the IBIEM governing equation using particle swarm optimization and artificial neural networks,replacing empirical judgment with data-driven methods to handle the uncertainty in the construction process.The reliability of the proposed model is validated by simulating the scattering of plane SH waves in a two-dimensional canyon using IBIEM.The results show that the proposed model can effectively predict the optimal placement and quantity of virtual wave sources,while balancing computational efficiency and accuracy,significantly improving the stability and efficiency of IBIEM in solving wave propagation problems.The optimal placement and quantity of virtual wave sources are significantly influenced by the incident wave frequency and the geometric conditions of the site,exhibiting non-monotonic characteristics.Empirical-based solutions have poor reliability,while data-driven prediction models have clear advantages.The proposed method can provide references for solving other types of seismic wave propagation problems using IBIEM. |
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